Bayesian jackknife tests with a small number of subsets: application to HERA 21 cm power spectrum upper limits

MJ Wilensky; F Kennedy; P Bull; JS Dillon; Z Abdurashidova; T Adams; JE Aguirre; P Alexander; ZS Ali; R Baartman; Y Balfour; AP Beardsley; G Bernardi; TS Billings; JD Bowman; RF Bradley; J Burba; S Carey; CL Carilli; C Cheng; DR Deboer; E De Lera Acedo; M Dexter; N Eksteen; J Ely; A Ewall-Wice; N Fagnoni; R Fritz; SR Furlanetto; K Gale-Sides; B Glendenning; D Gorthi; B Greig; J Grobbelaar; Z Halday; BJ Hazelton; JN Hewitt; J Hickish; DC Jacobs; A Julius; M Kariseb; NS Kern; J Kerrigan; P Kittiwisit; SA Kohn; M Kolopanis; A Lanman; P La Plante; A Liu; A Loots; DHE Macmahon; L Malan; C Malgas; K Malgas; B Marero; ZE Martinot; A Mesinger; M Molewa; MF Morales; T Mosiane; SG Murray; AR Neben; B Nikolic; H Nuwegeld; AR Parsons; N Patra; S Pieterse; N Razavi-Ghods; J Robnett; K Rosie; P Sims; H Swarts; N Thyagarajan; P Van Wyngaarden; PKG Williams; H Zheng

Journal article

Bayesian jackknife tests with a small number of subsets: application to HERA 21 cm power spectrum upper limits

MJ Wilensky, F Kennedy, P Bull, JS Dillon, Z Abdurashidova, T Adams, JE Aguirre, P Alexander, ZS Ali, R Baartman, Y Balfour, AP Beardsley, G Bernardi, TS Billings, JD Bowman, RF Bradley, J Burba, S Carey, CL Carilli, C Cheng Show all

Monthly Notices of the Royal Astronomical Society | OXFORD UNIV PRESS | Published : 2023

DOI: 10.1093/mnras/stac3484

Abstract

We present a Bayesian jackknife test for assessing the probability that a data set contains biased subsets, and, if so, which of the subsets are likely to be biased. The test can be used to assess the presence and likely source of statistical tension between different measurements of the same quantities in an automated manner. Under certain broadly applicable assumptions, the test is analytically tractable. We also provide an open-source code, chiborg, that performs both analytic and numerical computations of the test on general Gaussian-distributed data. After exploring the information theoretical aspects of the test and its performance with an array of simulations, we apply it to data from..

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University of Melbourne Researchers

Bradley Greig Author

Related Projects (1)

ARC CENTRE OF EXCELLENCE FOR ALL SKY ASTROPHYSICS IN 3D (ASTRO 3D)

Grants

Awarded by Horizon 2020 Framework Programme

Funding Acknowledgements

This material is based upon work supported by the National Science Foundation under grants #1636646 and #1836019 and institutional support from the HERA collaboration partners. This research is funded in part by the Gordon and Betty Moore Foundation through Grant GBMF5212 to the Massachusetts Institute of Technology. HERA is hosted by the South African Radio Astronomy Observatory, which is a facility of the National Research Foundation, an agency of the Department of Science and Innovation. This result is part of a project that has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. 948764; PB and MJW). PB and FK acknowledge support from STFC Grant ST/T000341/1. JSD gratefully acknowledges the support of the NSF AAPF award #1701536. NK gratefully acknowledges support from the MIT Pappalardo fellowship. PK and MGS acknowledge support from the South African Radio Astronomy Observatory (SARAO; www.sarao.ac.za) and the National Research Foundation (Grant No. 84156). YQ would like to acknowledge the support from the High Performance Computing centers of the Scuola Normale Superiore (Italy), the Council for Scientific and Industrial Research (South Africa), the OzSTAR national facility (Australia), and XSEDE (U.S.) for computational resources. JM acknowledges computational resources and support on the supercomputer Cedar at Simon Fraser University, which is managed by Compute Canada and funded by the Canada Foundation for Innovation (CFI). Parts of this research were supported by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013. SH acknowledges support from STFC studentship 2277533 in project ST/T505985/1. JBM is supported by a Clay Fellowship at the Smithsonian Astrophysical Observatory. GB acknowledges funding from the INAF PRIN-SKA 2017 project 1.05.01.88.04 (FORECaST), support from the Ministero degli Affari Esteri e della Cooperazione Internazionale - Direzione Generale per la Promozione del Sistema Paese Progetto di Grande Rilevanza ZA18GR02, and the National Research Foundation of South Africa (Grant Number 113121) as part of the ISARP RADIOSKY2020 Joint Research Scheme, from the Royal Society and the Newton Fund under grant NA150184, and from the National Research Foundation of South Africa (grant No. 103424). EdLA acknowledges the funding support of the UKRI Science and Technology Facilities Council SKA grant. AL acknowledges support from the New Frontiers in Research Fund Exploration grant program, the Canadian Institute for Advanced Research (CIFAR) Azrieli Global Scholars program, a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant and a Discovery Launch Supplement, the Sloan Research Fellowship, and the William Dawson Scholarship at McGill.